The fastest way to trust a generated API is not to read the code and not even to run its tests locally; it is to make the code stand up as an actual HTTP server and answer real requests before you let it anywhere near a merge request. Most failures in LLM-generated backend code hide between static correctness and runtime truth: a missing dependency that only matters when the process starts, an assumption about a default host, a path parameter that works in pseudocode but not in the framework's route parser, or a response shape that drifts from what the client expects. A local unit test can pass while every one of those problems remains invisible, because the test never starts the process, binds a port, or sends a request over a socket.
The loop worth describing is deliberately narrow. Use a free model to draft a small HTTP endpoint from a short specification, then deploy that draft to a disposable server where you can send it real requests, observe the response, and decide whether the generated code deserves to become part of your project. MonkeyCode's free model access and free server option make that loop easy to try without paying for a host or hand-rolling a local container, but the workflow is useful with any model and any temporary runtime you already have. Disclosure: This article was prepared as part of MonkeyCode's product outreach.
